作者
Shini Renjith, A Sreekumar, M Jathavedan
发表日期
2020/8
图书
Advances in Intelligent Systems and Computing
卷号
1133
页码范围
1047-1065
出版商
Springer Nature Singapore Pte Ltd
简介
Almost all modern industries leverage data analytics to deal with various dimensions of their business like demand forecasting, targeted marketing, and supply chain planning. In addition to historic data, social media data has also become a prominent source of input for data analytics. The key challenges observed with social media data are its huge volume and high dimensions that need to be dealt with. Clustering is the proven strategy in data analytics to segregate the relevant data for processing and thereby reducing the impact of huge volume. Dimensionality corresponds to the diverse features of the data subject being represented. The application of dimensionality reduction techniques can help in reducing the computational intensiveness caused by the curse of dimensionality. This paper covers an experimental analysis using four popular dimensionality reduction techniques – two linear and two nonlinear …
学术搜索中的文章
S Renjith, A Sreekumar, M Jathavedan - International Conference on Artificial Intelligence and …, 2019